A Qualitative Literature Review on Linkage Techniques for Data Integration

dc.contributor.authorKruse, Felix
dc.contributor.authorHassan, Ahmad Pajam
dc.contributor.authorAwick, Jan-Philipp
dc.contributor.authorMarx Gómez, Jorge
dc.date.accessioned2020-01-04T07:21:45Z
dc.date.available2020-01-04T07:21:45Z
dc.date.issued2020-01-07
dc.description.abstractThe data linkage techniques ”entity linking” and ”record linkage” get rising attention as they enable the integration of multiple data sources for data, web, and text mining approaches. This has resulted in the development of numerous algorithms and systems for these techniques in recent years. The goal of this publication is to provide an overview of these numerous data linkage techniques. Most papers deal with record linkage and structured data. Processing unstructured data through entity linking is rising attention with the trend Big Data. Currently, deep learning algorithms are being explored for both linkage techniques. Most publications focus their research on a single process step or the entire process of ”entity linking” or ”record linkage”. However, the papers have the limitation that the used approaches and techniques have always been optimized for only a few data sources.
dc.format.extent11 pages
dc.identifier.doihttps://doi.org/10.24251/HICSS.2020.132
dc.identifier.isbn978-0-9981331-3-3
dc.identifier.urihttp://hdl.handle.net/10125/63871
dc.language.isoeng
dc.relation.ispartofProceedings of the 53rd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectData, Text, and Web Mining for Business Analytics
dc.subjectbig data integration
dc.subjectdata science
dc.subjectentity linking
dc.subjectlinkage techniques
dc.subjectrecord linkage
dc.titleA Qualitative Literature Review on Linkage Techniques for Data Integration
dc.typeConference Paper
dc.type.dcmiText

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
0106.pdf
Size:
244.79 KB
Format:
Adobe Portable Document Format